Abstract: Systems and methods for optimal load distribution and data processing of a plurality of files in anti-malware solutions are provided herein. In some embodiments, the system includes: a plurality of node processors; a control processor programmed to: receiving a plurality of files used for malware analysis and training of anti-malware ML models; separating the plurality of files into a plurality of subsets of files based on byte size of each of the files, such that processing of each subset of files produces similar workloads amongst all available node processors; distributing the plurality of subsets of files amongst all available node processors such that each node processor processes its respective subset of files in parallel and within a similar timeframe as the other node processors; and receiving, by the control processor, a report of performance and/or anti-malware processing results of the subset of files performed from each node processor.

Abstract: Implementations for adaptive context sensitive time division multiplexed scheduling and execution of tasks to be performed by a high frequency ablation system, such as an RF ablation system, are disclosed. The implementations may be effectuated in software, firmware, or both. Tasks may be categorized into categories corresponding to task priorities. Time blocks may be allocated during which execution of the tasks may be performed. The time blocks may be divided into time slots. A task may be assigned to a time slot based, at least in part, on a categorization priority of the task. Additionally, each task may be executed according to the schedule delineated by the time slots. An assignment of tasks to time slots may be adjusted based, at least in part, on data received at a high frequency ablation device of the high frequency ablation system.

Abstract: System and method are described for copying and pasting files and folders between a client and a virtual desktop via clipboard redirection. A virtual desktop session can be established by the client on the virtual desktop. The user can copy a file or folder to the virtual desktop clipboard and a path corresponding to the file or folder can be stored in the virtual desktop clipboard in a path list. When the user ungrabs the agent or switches focus out of the virtual desktop to the client, the path list can be transferred to the client device and set into the client clipboard. Subsequently, a request can be received in the client device to paste the copied file or folder to a target location in the client device. In response to the request, the client device can retrieve the contents of the copied file or folder from the agent and the contents can be placed in the target location to complete the paste operation.

Abstract: A monitoring utility program into a software container in which a containerized virtual machine application is running. The monitoring utility program is to monitor the containerized virtual machine application running within the software container. Monitoring information regarding the containerized virtual machine application is periodically pulled from the monitoring utility program.

Abstract: An example method of managing guest time for a virtual machine (VM) supported by a hypervisor of a virtualized host computer includes: configuring, by the hypervisor, a central processing unit (CPU) of the host computer to trap, to the hypervisor, access by guest code in the VM to a physical counter and timer of the CPU; configuring, by the hypervisor, the guest code in the VM to use the physical counter and timer of the CPU rather than a virtual counter and timer of the CPU; trapping, at the hypervisor, an access to the physical counter and timer by the guest code; and executing, by the hypervisor, the access to the physical counter and timer on behalf of the guest code while compensating for an adjustment of a system count of the physical counter and timer to maintain the guest time as scaled with respect to frequency of the physical counter and timer.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to relocate a compute thread, the apparatus comprising control circuitry to maintain a location of a plurality of domain access counters associated with a plurality of compute-memory domains for a first compute thread, and an execution monitor to set a first domain access counter of the plurality of domain access counters, the first domain access counter associated with a first compute-memory domain of the compute-memory domains, and relocate the first compute thread to a second compute-memory domain of the compute-memory domains in response to a comparison between a second domain access counter associated with the second compute-memory domain and the first domain access counter.

Abstract: In variants, a method for robotic process automation (RPA) includes: receiving an automation request; optionally determining an application representation of an application associated with the automation request; generating a set of tasks based on the automation request; optionally classifying each task in the set of tasks; generating a set of instructions for each task in the set of tasks; optionally validating the set of instructions; and optionally executing the set of instructions cooperatively forming an RPA bot.

Abstract: A determination is made as to whether a value of a first parameter of a first application is to be obtained using a natural language interaction. Based on received input, a first service of a plurality of services is identified. The first service is to be used to perform a first task associated with the first parameter. Portions of the first application to determine the value of the first parameter and to invoke the first service are generated.

Abstract: A task execution method using resources includes receiving an execution request for a first task; analyzing the first task and dividing the first task into a plurality of sub-tasks; identifying a sub-task using a first neural network from among the sub-tasks and dividing the identified sub-task into a plurality of layer tasks corresponding to calculations between layers constituting the first neural network; calculating a deadline time of each of the sub-tasks; scheduling a first sub-task to be scheduled to a first resource group from among the resources; and, when a runtime of the first sub-task exceeds a deadline time of the first sub-task, scheduling a sub-task or a layer task subsequent to the first sub-task to a second resource group.

Abstract: Multi-cloud deployment strategy is based on automated analysis of context and requirements for an activity workload. The activity workload is defined by user input including information regarding project cost, performance requirements, and geographical preferences. Selection of cloud-based resources for handling the activity workload is based in part on service availability record, projected cost of resources, and physical geographic locations. A cloud services registry provides cloud service provider data for selection to perform aspects of the activity workload.

Abstract: In accordance with embodiments disclosed herein, there are provided mechanisms and methods for automating deployment of applications in a multi-tenant database environment. For example, in one embodiment, mechanisms include managing a plurality of machines operating as a machine farm within a datacenter by executing an agent provisioning script at a control hub, instructing the plurality of machines to download and instantiate a lightweight agent; pushing a plurality of URL (Uniform Resource Locator) references from the control hub to the instantiated lightweight agent on each of the plurality of machines specifying one or more applications to be provisioned and one or more dependencies for each of the applications; and loading, via the lightweight agent at each of the plurality of machines, the one or more applications and the one or more dependencies for each of the one or more applications into memory of each respective machine.

Abstract: A computer system, processor, programming instructions and/or method for balancing the workload of processing pipelines that includes an execution slice, the execution slice comprising at least two processing pipelines having one or more execution units for processing instructions, wherein at least a first processing pipeline and a second processing pipeline are capable of executing a first instruction type; and an instruction decode unit for decoding instructions to determine which of the first processing pipeline or the second processing pipeline to execute the first instruction type. The processor configured to calculate at least one of a workload group consisting of: the first processing pipeline workload, the second processing pipeline workload, and combinations thereof; and select the first processing pipeline or the second processing pipeline to execute the first instruction type based upon at least one of the workload group.

Abstract: A system can determine to restore a datacenter that comprises a group of virtualized workloads. The system can determine respective associations between respective virtualized workloads and respective datastores. The system can determine to restore a first virtualized workload of the group of virtualized workloads first. The system can restore a first portion of infrastructure that corresponds to the first virtualized workload first among a group of infrastructure. The system can, after restoring the first portion of infrastructure, restore a first portion of data that corresponds to the first virtualized workload first among a group of data. The system can, after restoring the first portion of data, restore a first portion of a virtualization layer that corresponds to the first virtualized workload first among a group of virtualization layers. The system can, after restoring the first portion of the virtualization layer, restore the first virtualized workload.

Abstract: A computer system executes a database management system (DBMS). The DBMS manages a database comprised of DBMS resources. The DBMS receives a request to be executed. The request is a DBMS action to be executed using the DBMS resources. The request includes a predicate specifying a maximum cost for executing the request, and a deadline, specifying a deadline by which the request is to be completed in its execution. The DBMS determines a plurality of workloads under which the request is qualified to execute. Each workload of the plurality of workloads includes a respective set of requests that have common characteristics. Each workload of the plurality of workloads includes a respective cost criterion and a respective elapsed time criterion. The DBMS selects a selected workload from among the plurality of workloads. The selected workload has a selected cost criterion and a selected elapsed time criterion. The DBMS begins execution of the request using the selected workload.

Abstract: A virtualization infrastructure control apparatus (10) includes an operation parameter monitoring unit (122) configured to acquire an operation parameter, a resource monitoring unit (121) configured to acquire predetermined load information, and a migration determination unit (111). The migration determination unit (111) determines to execute live migration when the migration determination unit (111) determines that the operation parameter satisfies a predetermined operation condition and that a load is low by comparing a predetermined load information with a predetermined threshold, whereas the migration determination unit (111) determines to execute healing when the migration determination unit (111) determines that the operation parameter does not satisfy the predetermined operation condition or that the load is high by comparing the predetermined load information with the predetermined threshold.

Abstract: A disclosed method provides a migration service, executable within a hypervisor, configured to calculate, based on a plurality of migration tenets, a migration value for an application running in a VM supported by the hypervisor. If the calculated migration value exceeds a threshold value, a migration tool is invoked to migrate the virtualized application to a functionally equivalent containerized application. The migration value for a VM based application may be determined by calculating a plurality of tenet scores corresponding to a plurality of migration tenets. Each tenant score may equal a sum of scores for each of one or more attributes associated with each tenet. Weightings may be assigned to each tenet such that the migration value is the sum of weighted tenet values. The tenets may include, as non-limiting examples, a security tenet, a density/performance tenet, and a high availability tenet.

Abstract: This on-vehicle control device includes: an acquisition unit configured to acquire a plurality of pieces of wear information regarding a degree of wear of each of a plurality of function units mounted on a vehicle; a selection unit configured to select, on the basis of each piece of the wear information acquired by the acquisition unit, from the plurality of function units, one or a plurality of the function units to be caused to perform a target process that should be performed by one or a plurality of the function units among the plurality of function units; and a control unit configured to perform a control of causing the one or plurality of the function units selected by the selection unit to perform the target process.

Abstract: In a M2M device management system, a Task Orchestration Module, TOM (32) external to the M2M device (20) manages the execution of tasks wholly or partly on the M2M device (20). This alleviates the M2M device (20) of the need to store code, execute tasks, monitor task execution, and the like. The tasks are specified using Finite State Machine, FSM, syntax. A task URL, tURL (34) resource on the M2M device (20) provides a tURL (34) to a resource hosting (36) a service (38) mapping task-IDs to FSM specifications. Communications between the TOM (32) and M2M device (20) is compactly and efficiently achieved using a device management protocol server/client system (16, 18), such as LightWeightM2M (LWM2M). A predetermined mapping (40) at the M2M device (20) maps action labels to library functions (22) of the M2M device (20), obviating the need for code in the M2M device (20) to interpret and execute actions.

Abstract: Disclosed embodiments relate to controlling sets of graphics work (e.g., kicks) assigned to graphics processor circuitry. In some embodiments, tracking slot circuitry implements entries for multiple tracking slots. Slot manager circuitry may store, using an entry of the tracking slot circuitry, software-specified information for a set of graphics work, where the information includes: type of work, dependencies on other sets of graphics work, and location of data for the set of graphics work. The slot manager circuitry may prefetch, from the location and prior to allocating shader core resources for the set of graphics work, configuration register data for the set of graphics work. Control circuitry may program configuration registers for the set of graphics work using the prefetched data and initiate processing of the set of graphics work by the graphics processor circuitry according to the dependencies. Disclosed techniques may reduce kick-to-kick transition time, in some embodiments.

Abstract: Implementations are disclosed for adaptively reallocating computing resources of resource-constrained devices between tasks performed in situ by those resource-constrained devices. In various implementations, while the resource-constrained device is transported through an agricultural area, computing resource usage of the resource-constrained device ma may be monitored. Additionally, phenotypic output generated by one or more phenotypic tasks performed onboard the resource-constrained device may be monitored. Based on the monitored computing resource usage and the monitored phenotypic output, a state may be generated and processed based on a policy model to generate a probability distribution over a plurality of candidate reallocation actions.